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math.OC2026
Automating Reformulation for Parallel ADMM
Kaizhao Sun, Baihao Wu, Kun Yuan +1
Many real-world optimization models contain exploitable sparsity and block structure, but this structure is often obscured in algebraic form, limiting the effectiveness of modern p…
math.OC2024
Learning to optimize: A tutorial for continuous and mixed-integer optimization
Xiaohan Chen, Jialin Liu, Wotao Yin
Learning to Optimize (L2O) stands at the intersection of traditional optimization and machine learning, utilizing the capabilities of machine learning to enhance conventional optim…
math.OC2024
Efficient Algorithms for Sum-of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang +1
In this work, we propose a novel optimization model termed "sum-of-minimum" optimization. This model seeks to minimize the sum or average of objective functions over parame…